“Novel Analytics from James Joyce to the Bestseller Code”

In a New Yorker article in 2014, Joshua Rothman asks, provocatively and rhetorically: “If you’re an English professor, how should you spend your time: producing [close] ‘readings’ of the literary works that you care about (art), or looking for the [distant] patterns that shape whole literary forms or periods (science)?” Rothman’s parentheticals, “art” and “science,” make for a good editorial hook, but they frame a misleading and false dichotomy. The emerging debate in literary studies pitting traditional scholarly practices of close reading against digitally oriented methods of “distant” reading is a nonstarter. What gets disguised as an argument over method (close vs. distant) and discipline (art vs. science) is, in fact, an argument about interpretation and the ways that literary scholars collect and prioritize evidence. In this talk Jockers proposes a methodological reconciliation that understands large scale computational approaches to literature as entirely consistent with traditional practices of close reading.